Food consumption plays a pivotal role in shaping our environmental footprint, particularly concerning carbon dioxide (CO2) emissions. The choices we make at the dinner table extend far beyond mere sustenance; they resonate deeply with our planet’s health. With the global population soaring and dietary habits evolving, understanding the nexus between food consumption and CO2 emissions has become imperative. From the production and distribution of food to its preparation and eventual disposal, every aspect of the food cycle emits varying levels of CO2.
This script aims to analyze CO2 emissions from food consumption across different countries. It provides insights into the relationship between food consumption patterns and associated CO2 emissions, as well as comparisons between different food categories and countries.
For the purpose of this small study, we will be seeing the relation between Consumption of Food and their CO2 Emissions. The Food Products have been divided into 11 broad categories, and we consider a further breakdown on the basis of the Country of consumption.
A preview and summary of the dataset is as follows.
## # A tibble: 6 × 4
## country food_category consumption co2_emmission
## <chr> <chr> <dbl> <dbl>
## 1 Argentina Pork 10.5 37.2
## 2 Argentina Poultry 38.7 41.5
## 3 Argentina Beef 55.5 1712
## 4 Argentina Lamb & Goat 1.56 54.6
## 5 Argentina Fish 4.36 6.96
## 6 Argentina Eggs 11.4 10.5
## country food_category consumption co2_emmission
## Length:1430 Length:1430 Min. : 0.000 Min. : 0.00
## Class :character Class :character 1st Qu.: 2.365 1st Qu.: 5.21
## Mode :character Mode :character Median : 8.890 Median : 16.53
## Mean : 28.110 Mean : 74.38
## 3rd Qu.: 28.133 3rd Qu.: 62.60
## Max. :430.760 Max. :1712.00
## [1] 1430 4
The dataset has been cleaned and checked for ‘na’ values. There is no requirement of feature scaling at this stage. This is a brief analysis and will not focus on predictions or classifications.
These box plots give us a brief idea of the distributions of the Food Consumption and CO2 Emissions. The plot shows that the distributions are not proportionate and that there is a higher level of emissions when compared to the consumptions.
We have used log values for this plot. This allows us to get better comparability.
Even though these box plots are fairly representative, let us add the actual datapoints to get better visibility of the density of the distribution.
The dataset has two predefinied coloumns that show us the Consumption and CO2 Emissions. The data is on a per person per Kg basis.
Consumption = Kg of Food Ate by Each Person
CO2 Emission = Kg of CO2 Produced by Each Person
Let us use this information to answer the question “For every KG of Food that is consumed, how many KG’s of CO2 is emitted?”.
This graph gives us an idea of the breakdown of the amount of emission per KG of food consumed, broken down by category.
Based on this graph, ‘Lamb & Goat’ & ‘Beef’ are the two broad categories that produce the maximum amount of CO2 Emissions per KG consumed.
Let us visualize the CO2 Emissions from a global perspective.
This gives us a good perspective of the scale of emissions from across the globe. We can see that the level of emissions are higher from historically meat eating countries. But this map does not provide an intuitive approach to understanding total emissions.
For the purpose of this project, the data has been represented on a globe as well. This will allow for better navigation.
The globe is a representation of the total CO2 Emissions by each country. The “Greener” the country, the lesser are the CO2 Emissions.
Let us see the top 5 consuming countries grouped for different food categories.
## # A tibble: 55 × 2
## # Groups: food_category [11]
## country food_category
## <chr> <chr>
## 1 Argentina Beef
## 2 Brazil Beef
## 3 USA Beef
## 4 Australia Beef
## 5 Bermuda Beef
## 6 Japan Eggs
## 7 Paraguay Eggs
## 8 China Eggs
## 9 Mexico Eggs
## 10 Ukraine Eggs
## # ℹ 45 more rows
The list of top 5 countries would not be the best representation for this brief analysis. Let us compare the top consumer country from each food category.
##
##
## Table: Top Consumer Across Food Categories
##
## |Country |Food Category |
## |:--------------------|:------------------------|
## |Argentina |Beef |
## |Japan |Eggs |
## |Maldives |Fish |
## |Iceland |Lamb & Goat |
## |Finland |Milk - inc. cheese |
## |United Arab Emirates |Nuts inc. Peanut Butter |
## |Hong Kong SAR. China |Pork |
## |Israel |Poultry |
## |Bangladesh |Rice |
## |Taiwan. ROC |Soybeans |
## |Tunisia |Wheat and Wheat Products |
This list gives us a perspective of the top consumed food and this also has corroborates the global heatmap, eg: Argentina being the biggest consumer of beef has one of the highest CO2 emissions.
Let us get a better perspective of the overall CO2 Emissions and Food consumption habits of various countries.
For this purpose, we will see the countries that appear more than once in the Top 5 list.
##
##
## Table: Countries With More Than 1 Appearance In Top 5
##
## |Country | Number Of Appearances|
## |:--------------------|---------------------:|
## |Hong Kong SAR. China | 3|
## |Albania | 2|
## |Iceland | 2|
## |Japan | 2|
## |Kuwait | 2|
## |Maldives | 2|
## |Myanmar | 2|
Most of the countries from this list are situated in the Asia and Middle East region. This can be attributed to the concentration of population that has both Vegeterian and Non-Vegeterian Dietary habits.
There is a significant cultural aespect involved in the Food Consumption habits and further analysis can be done based on the habits of the population.
We can do a cursory comparison of “Animal Based” and “Non-Animal Based” food products based on the given categories.
The following table shows us the breakdown of the top food categories by total consumption. The table also includes whether the food category is animal based or not.
##
##
## Table: Top Food Categories By Consumption
##
## |Food Category |Vegan/Non-Vegan |
## |:------------------------|:------------------|
## |Milk - inc. cheese |Animal Product |
## |Rice |Non-Animal Product |
## |Wheat and Wheat Products |Non-Animal Product |
## |Fish |Animal Product |
The Top two highest categories by consumption are generally included in the staple diets across geographies. Especially in Asia and the Middle East. This corroborates our initial result of top consuming country by food category.
Let us further compare the food categories by emission and whether they are animal based.
##
##
## Table: Top Food Categories By Emission
##
## |Food Category |Vegan/Non-Vegan |
## |:------------------|:------------------|
## |Beef |Animal Product |
## |Milk - inc. cheese |Animal Product |
## |Lamb & Goat |Animal Product |
## |Rice |Non-Animal Product |
The same result was previouly obtained when reviewing the descriptive statistics.
Let us compare the above two tables graphically.
Based on this graph we can see that Non Animal products have a higher consumption, but the emissions peak comparatively earlier than Animal Products.
The consumption of Animal Products is not as consistent, but the emissions are consistent with the rate of consumption.
In conclusion, this script sheds light on the intricate relationship between food consumption patterns and CO2 emissions. As evident from the analysis, food consumption habits impact environmental sustainability, with certain food categories contributing more to CO2 emissions than others.
The comparison of emissions per unit of consumption reveals that animal-based food products, such as beef and lamb, tend to have higher emissions compared to non-animal-based products.
Additionally, the visualization of CO2 emissions on a global scale highlights the geographical distribution of emissions, with countries known for meat consumption showing higher emissions levels.
Moreover, the examination of top-consuming countries and food categories provides insights into dietary preferences and their environmental implications.
Furthermore, the comparison between animal and non-animal-based products underscores the need for sustainable food production practices and dietary shifts towards plant-based alternatives to reduce emissions.
Overall, this analysis highlights the role of food consumption in driving CO2 emissions. It can act as a basis for further study to emphasizes the urgency of adopting sustainable dietary patterns to mitigate climate change.
This is a cursory analysis and should be used as a basis for further study.